From ad1b3d7518429e2d16a2695d9b0bbf81b6565ac9 Mon Sep 17 00:00:00 2001 From: Teresa Charlin Date: Tue, 14 Mar 2023 12:10:28 +0000 Subject: IVGCVSW-7555 Restructure Delegate * New folders created: * common is for common code where TfLite API is not used * classic is for existing delegate implementations * opaque is for new opaque delegate implementation, * tests is for shared between existing Delegate and Opaque Delegate which have test utils to work which delegate to use. * Existing delegate is built to libarmnnDelegate.so and opaque delegate is built as libarmnnOpaqueDelegate.so * Opaque structure is introduced but no API is added yet. * CmakeList.txt and delegate/CMakeList.txt have been modified and 2 new CmakeList.txt added * Rename BUILD_ARMNN_TFLITE_DELEGATE as BUILD_CLASSIC_DELEGATE * Rename BUILD_ARMNN_TFLITE_OPAQUE_DELEGATE as BUILD_OPAQUE_DELEGATE Signed-off-by: Teresa Charlin Change-Id: Ib682b9ad0ac8d8acdc4ec6d9099bb0008a9fe8ed --- delegate/test/PackTestHelper.hpp | 186 +++++++++++++++++++++++++++++++++++++++ 1 file changed, 186 insertions(+) create mode 100644 delegate/test/PackTestHelper.hpp (limited to 'delegate/test/PackTestHelper.hpp') diff --git a/delegate/test/PackTestHelper.hpp b/delegate/test/PackTestHelper.hpp new file mode 100644 index 0000000000..0fd2f195f4 --- /dev/null +++ b/delegate/test/PackTestHelper.hpp @@ -0,0 +1,186 @@ +// +// Copyright © 2021, 2023 Arm Ltd and Contributors. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#pragma once + +#include "TestUtils.hpp" + +#include + +#include +#include +#include +#include +#include +#include + +#include + +#include + +namespace +{ + +std::vector CreatePackTfLiteModel(tflite::BuiltinOperator packOperatorCode, + tflite::TensorType tensorType, + std::vector& inputTensorShape, + const std::vector & outputTensorShape, + const int32_t inputTensorNum, + unsigned int axis = 0, + float quantScale = 1.0f, + int quantOffset = 0) +{ + using namespace tflite; + flatbuffers::FlatBufferBuilder flatBufferBuilder; + + std::vector> buffers; + buffers.push_back(CreateBuffer(flatBufferBuilder)); + buffers.push_back(CreateBuffer(flatBufferBuilder)); + + auto quantizationParameters = + CreateQuantizationParameters(flatBufferBuilder, + 0, + 0, + flatBufferBuilder.CreateVector({ quantScale }), + flatBufferBuilder.CreateVector({ quantOffset })); + + std::vector operatorInputs{}; + const std::vector operatorOutputs{inputTensorNum}; + std::vector subgraphInputs{}; + const std::vector subgraphOutputs{inputTensorNum}; + + std::vector> tensors(inputTensorNum + 1); + for (int i = 0; i < inputTensorNum; ++i) + { + tensors[i] = CreateTensor(flatBufferBuilder, + flatBufferBuilder.CreateVector(inputTensorShape.data(), + inputTensorShape.size()), + tensorType, + 1, + flatBufferBuilder.CreateString("input" + std::to_string(i)), + quantizationParameters); + + // Add number of inputs to vector. + operatorInputs.push_back(i); + subgraphInputs.push_back(i); + } + + // Create output tensor + tensors[inputTensorNum] = CreateTensor(flatBufferBuilder, + flatBufferBuilder.CreateVector(outputTensorShape.data(), + outputTensorShape.size()), + tensorType, + 0, + flatBufferBuilder.CreateString("output"), + quantizationParameters); + + // create operator + tflite::BuiltinOptions operatorBuiltinOptionsType = tflite::BuiltinOptions_PackOptions; + flatbuffers::Offset operatorBuiltinOptions = + CreatePackOptions(flatBufferBuilder, inputTensorNum, axis).Union(); + + flatbuffers::Offset packOperator = + CreateOperator(flatBufferBuilder, + 0, + flatBufferBuilder.CreateVector(operatorInputs.data(), operatorInputs.size()), + flatBufferBuilder.CreateVector(operatorOutputs.data(), operatorOutputs.size()), + operatorBuiltinOptionsType, + operatorBuiltinOptions); + + flatbuffers::Offset subgraph = + CreateSubGraph(flatBufferBuilder, + flatBufferBuilder.CreateVector(tensors.data(), tensors.size()), + flatBufferBuilder.CreateVector(subgraphInputs.data(), subgraphInputs.size()), + flatBufferBuilder.CreateVector(subgraphOutputs.data(), subgraphOutputs.size()), + flatBufferBuilder.CreateVector(&packOperator, 1)); + + flatbuffers::Offset modelDescription = + flatBufferBuilder.CreateString("ArmnnDelegate: Pack Operator Model"); + flatbuffers::Offset operatorCode = CreateOperatorCode(flatBufferBuilder, packOperatorCode); + + flatbuffers::Offset flatbufferModel = + CreateModel(flatBufferBuilder, + TFLITE_SCHEMA_VERSION, + flatBufferBuilder.CreateVector(&operatorCode, 1), + flatBufferBuilder.CreateVector(&subgraph, 1), + modelDescription, + flatBufferBuilder.CreateVector(buffers.data(), buffers.size())); + + flatBufferBuilder.Finish(flatbufferModel); + + return std::vector(flatBufferBuilder.GetBufferPointer(), + flatBufferBuilder.GetBufferPointer() + flatBufferBuilder.GetSize()); +} + +template +void PackTest(tflite::BuiltinOperator packOperatorCode, + tflite::TensorType tensorType, + std::vector& backends, + std::vector& inputShape, + std::vector& expectedOutputShape, + std::vector>& inputValues, + std::vector& expectedOutputValues, + unsigned int axis = 0, + float quantScale = 1.0f, + int quantOffset = 0) +{ + using namespace tflite; + std::vector modelBuffer = CreatePackTfLiteModel(packOperatorCode, + tensorType, + inputShape, + expectedOutputShape, + inputValues.size(), + axis, + quantScale, + quantOffset); + + const Model* tfLiteModel = GetModel(modelBuffer.data()); + + // Create TfLite Interpreters + std::unique_ptr armnnDelegateInterpreter; + CHECK(InterpreterBuilder(tfLiteModel, ::tflite::ops::builtin::BuiltinOpResolver()) + (&armnnDelegateInterpreter) == kTfLiteOk); + CHECK(armnnDelegateInterpreter != nullptr); + CHECK(armnnDelegateInterpreter->AllocateTensors() == kTfLiteOk); + + std::unique_ptr tfLiteInterpreter; + CHECK(InterpreterBuilder(tfLiteModel, ::tflite::ops::builtin::BuiltinOpResolver()) + (&tfLiteInterpreter) == kTfLiteOk); + CHECK(tfLiteInterpreter != nullptr); + CHECK(tfLiteInterpreter->AllocateTensors() == kTfLiteOk); + + // Create the ArmNN Delegate + armnnDelegate::DelegateOptions delegateOptions(backends); + std::unique_ptr + theArmnnDelegate(armnnDelegate::TfLiteArmnnDelegateCreate(delegateOptions), + armnnDelegate::TfLiteArmnnDelegateDelete); + CHECK(theArmnnDelegate != nullptr); + + // Modify armnnDelegateInterpreter to use armnnDelegate + CHECK(armnnDelegateInterpreter->ModifyGraphWithDelegate(theArmnnDelegate.get()) == kTfLiteOk); + + // Set input data for all input tensors. + for (unsigned int i = 0; i < inputValues.size(); ++i) + { + // Get single input tensor and assign to interpreters. + auto inputTensorValues = inputValues[i]; + armnnDelegate::FillInput(tfLiteInterpreter, i, inputTensorValues); + armnnDelegate::FillInput(armnnDelegateInterpreter, i, inputTensorValues); + } + + // Run EnqueWorkload + CHECK(tfLiteInterpreter->Invoke() == kTfLiteOk); + CHECK(armnnDelegateInterpreter->Invoke() == kTfLiteOk); + + // Compare output data + armnnDelegate::CompareOutputData(tfLiteInterpreter, + armnnDelegateInterpreter, + expectedOutputShape, + expectedOutputValues); + + armnnDelegateInterpreter.reset(nullptr); +} + +} // anonymous namespace \ No newline at end of file -- cgit v1.2.1